Continuous volume detection for a reservoir in a fluid circuit of a medical system

ABSTRACT

Continuous volume detection for a reservoir in a fluid circuit of a medical system is described. Volume detection is based on a pressure measurement that is manipulated via application of fluid mechanics. Next-generation medical system controllers may use this data to control the volume contained in the reservoir.

CROSS-REFERENCE TO RELATED APPLICATIONS

This Application is a Continuation of Ser. No. 10/957,528, filed Oct. 1,2004, which claims the benefit of U.S. Provisional Application No.60/507,993, filed Oct. 2, 2003, the entire contents of each beingincorporated herein by reference.

TECHNICAL FIELD

The invention relates to medical systems.

BACKGROUND

During cardiopulmonary bypass surgery, blood must be oxygenated andcirculated artificially outside of the body. For external circulation tobe successful, it is critical to provide a method for passive venousdrainage and to prevent air bubbles from entering the bypass circuit. Ifan air bubble finds its way to the human brain, consequences includebrain damage and death. The venous reservoir component of thecardiopulmonary bypass circuit provides passive drainage, but isespecially susceptible to air bubble introduction. Two types ofreservoir exist, the flexible reservoir and the hard-sided reservoir. Aprimed flexible reservoir is much less likely to introduce bubbles intothe circuit than its counterpart, due to its ability to conform itsshape to accommodate the volume of blood in the reservoir.

Currently, level detection is available for the hard-sided reservoir inthe form of acoustic sensors that attach to the container. These sensorsare capable of determining whether or not fluid has reached a certainlevel. Due to its nature, this detection mechanism is not capable ofproviding continuous volume data.

Level detectors have taken on many forms throughout their evolution.Capacitance, weight, and light-based systems are a few of the leveldetection methods that experienced limited success. However, thesesystems were plagued with issues, as in the weight-based system, where“the tragic defect in this device is that the device cannotdifferentiate between blood in the arterial reservoir and someoneleaning on the weight arm. There have been reports of someone pushingdown on the arm, the arterial pump head going to maximum RPM, and airbeing pumped into the patient.”

In terms of benefits, electronic level sensing relieves the perfusionist(the person in charge of the bypass circuit) of the extraneous duty ofmonitoring the venous reservoir. By eliminating a task for theperfusionist, this system will also reduce the likelihood of humanerror.

SUMMARY

In general, the invention is directed to techniques for automaticallydetermining volume in a flexible venous reservoir by pressuremeasurements. The pressure-volume characteristics of a static reservoiris analyzed, and is used as a basis for evaluation of a dynamicenvironment in which fluid is flowing into and out of the venousreservoir. Bernoulli's principle for an ideal fluid is applied topredict the pressure response for this situation. The fluid flow of thesystem is measured, and is applied to accurately predict the pressuredrop introduced by fluid flow. The pressure can then be reconstructedand considered in a static sense.

The techniques described herein include, characterization of a flexiblereservoir pressure response, system integration to prove or dismissfeasibility, signal processing to remove pressure noise, and pressuredrop due to fluid flow. These and other techniques are described hereinwith respect to automatically determining volume in a flexible venousreservoir by pressure measurements.

The details of one or more embodiments of the invention are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the invention will be apparent from thedescription and drawings, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating an example embodiment of acardiopulmonary bypass circuit in which a controller applies thepressure-based level sensing techniques described herein.

FIG. 2 is a block diagram illustrating an exemplary embodiment of thecontroller of FIG. 1.

FIG. 3 displays an exemplary lab configuration used for evaluating thetechniques described herein.

FIGS. 4-11 are graphs.

FIG. 12 illustrates a circuit diagram of an active filter for use withinthe bypass circuit.

FIG. 13 is a chart illustrating the actual digital pulses used for thetiming of the tachometer.

DETAILED DESCRIPTION

FIG. 1 is a block diagram illustrating an example embodiment of acardiopulmonary bypass circuit in which a controller 4 applies thepressure-based level sensing techniques described herein. Asillustrated, the exemplary bypass circuit includes the followingelements: a person's elevated circulatory system, two cannulae thatroute blood into and out of the person's circulatory system, a venousreservoir for blood storage, a pump that provides blood flow, anoxygenator to oxygenate the blood, and an arterial filter to removeblood contaminants. It should be noted that this is a simplifiedrepresentation, and that there are many variations on the circuit.

In the illustrated embodiment, pressure sensor 8 is connected near anoutlet of the venous reservoir, and generates a pressure signal 10representative of the sensed pressure. In one embodiment, pressuresensor 8 is a diaphragm pressure sensor coupled to the outlet tubing viaa tap. Pressure sensor 8 may generate signal 10 an analog voltage sensoris connected near the bottom of the venous reservoir. The output voltageof pressure sensor 8 may be directly proportional to the pressuredetected by the sensor.

Flow sensor 16 generates signal 14 representative of a fluid velocity ofthe fluid exiting the venous reservoir. In the exemplary embodiment,flow sensor 16 is illustrated as positioned downstream from pressuresensor 8 for exemplary purposes. In other embodiments flow sensor 16 maybe positioned in other areas of the system.

As described in detail herein, controller 4 receives pressure signal 10and flow signal 14, and calculates a current volume of blood within thevenous reservoir. Based on the calculated volume, controller 4 mayoutput control signal 18 to provide automatic regulation of the pump 12,thereby dynamically adjusting the flow of blood through thecardiopulmonary bypass circuit. In addition, controller 4 may present anindicator of the current volume of blood contained within the venousreservoir. Controller 4 may, for example, present a graphicalrepresentation of soft or hard container, and a visual indicator of thecurrent blood level within the container. As other examples, controller4 may output an audible warning if the volume of blood within the venousreservoir drops to a programmably defined level.

In one embodiment, pump 12 may be a roller pump having an output signalthat represents the speed of the pump. Controller 4 may make use of thisspeed signal to calculate the blood flow velocity.

FIG. 2 is a block diagram illustrating an exemplary embodiment ofcontroller 4. In the illustrated embodiment, controller 4 includes aprocessor 20, a memory 22, an input device 24 and a display 26.

Memory 22 stores a set of container profiles 32, in which each profileas associated with a particular type of container for use as the venousreservoir. For example, a container profile may be created for each typeof hard container and/or soft container that may be used within thesystem. Each profile characterizes the respective container in a mannerthat allows controller 4 to accurately calculate the volume of bloodwith the venous reservoir. Each profile may, for example, store a set ofcoefficients for application by controller 4 to a polynomial thatuniquely maps pressure to the volume for the respective location. Thepolynomial mapping may comprise, for example, a 5^(th) order polynomial.

Memory 22 may also store other parameters that may be used during thevolume calculation. Example parameters include a distance from whichpressure sensor 8 is located from the outlet of the venous reservoir,and patient specific parameters, such as hematocrit characteristics ofthe patient that may influence blood viscosity.

Controller 4 receives programmable input, e.g., a current type of hardor soft container, position of pressure sensor 8, patient-specificattributes. Based on the programmable input, controller 4 selects one ofthe profiles 32, and calculates a current volume of blood within thevenous reservoir as a function of pressure signal 10 and flow signal 14.

In another embodiment, memory 22 may comprise a look-up table for whichvolume levels of the venous reservoir have been pre-calculated as afunction of bag type, sensed pressure, sensed flow velocity, and otherparameters.

Controller 4 presents on display 26 an indicator of the current volumeof blood contained within the venous reservoir. Controller 4 may, forexample, present a graphical representation of soft or hard container,and a visual indicator of the current blood level within the container.As other examples, controller 4 may output an audible warning if thevolume of blood within the venous reservoir drops to a programmablydefined level.

Controller 4 may include a secondary output port, e.g., a networkconnection, to communicate the computed volume to another medical deviceor system.

FIG. 3 displays an exemplary test lab configuration used for evaluatingthe techniques described herein. The flexible venous reservoir used wasa 1500 ml Sarns Flexible Venous Reservoir, which is hung from anadjustable vertical support. A clear plastic PVC pipe was calibrated andused as a 5 L graduated cylinder. Tube occlusion elements were used torestrict fluid flow into and out of each member.

Data analysis was performed using both Microsoft Excel 97 and MicrocalOrigin 5.0. Excel was used to store and manipulate data, calculatex-error compensation, and for quick trend analysis. Origin was used forits advanced curve fitting (3^(rd) and 5^(th) order polynomials) witherror weighting and three-dimensional graphing capabilities.

In order to resolve an accurate volume measurement for a particularpressure value, it was necessary to characterize the pressure-volumerelationship in the 1500 ml Sarns Flexible Venous Reservoir. Also, inthe clinical setting, it would be ideal to have a systematic approach tovolume detection system setup. To provide a systematic approach tosetup, a consistent way of zeroing the pressure sensor must beestablished, and is explored in this section.

Characterization of the reservoir was accomplished by gravity fillingthe reservoir from the graduated cylinder. The occluder, a passivedevice that attaches to the outside of the tubing in order to restrictflow, was carefully released to fill the reservoir with a precise volumeof water. The water was allowed time to stabilize, and a pressuremeasurement was taken a few inches from the reservoir outlet. To ensurerepeatability, data was taken three times for each of three differentreservoirs and compiled.

After reviewing the raw data, it was determined that the one method ofzeroing the pressure would be to concentrate on the area of minimalpressure change, which occurs throughout the middle of the reservoir'svolume. By offsetting the pressure such that the half-volume pointcorresponds to zero pressure, minimal error is introduced if the volumeis not exactly at the half-volume point. Also, measurement accuracywould not suffer potential pressure offsets introduced at the volumeextremes.

For curve fitting purposes, data was shifted on the x-axis such that thehalf-volume point was also centered at zero. This removes the offset ineach of the x parameters in a polynomial fit of the data. FIG. 4displays the pressure-volume response seen in characterization of thereservoir.

Techniques were developed to remove any pressure noise created by thecentrifugal pump that was used to introduce fluid flow to the system.Because the changes in our target signal (i.e. the reservoir'svolume-generated pressure) occur very slowly, only low frequencypressure signals were needed. The pressure signal was sampled by thehardware/software at 100 Hz. An analog low-pass filter with a 30 Hzcutoff and 6 dB/octave of attenuation was used on the front end toprevent aliasing. The remainder of the signal processing was done insoftware.

Because the reservoir is to be maintained throughout a bypass surgery,one can conclude that the volume in the reservoir is not allowed tochange rapidly. For this reason, a digital low-pass Butterworth filterwas designed with a cutoff frequency of 0.1 Hz. This cutoff frequencyallowed the filter to remain a 2nd order filter, while removing allunnecessary signals. Priority was given to keeping the filter's orderminimal because this algorithm could eventually find its way onto asmall 16-bit embedded microcontroller.

The effects of fluid flow introduction and re-building the pressurevalue by compensating for the pressure drop generated by fluid flow wereanalyzed.

Bernoulli's principle for an ideal fluid states that the pressure dropdue to fluid flow (i.e. kinetic energy per unit volume) can be found bythe following relationship:

P _(drop)=½ρv ²,

where ρ is the density of the fluid, and v is the velocity of the fluid.

Because fluid flow data is available in a network-based cardiopulmonarybypass circuit, we can use this fluid flow data in conjunction with thetubing's inside diameter to predict the velocity of the fluid in thetubing. All experiments were conducted using ⅜″ ID (inner diameter)tubing, which results in the following pressure drop function of flow:

P _(drop)(Flow)=0.0110 Flow^(2 [inH) ₂O],

where flow is in Liters per minute, and the Pressure Drop Coefficient isin inH2O-min2/L2.

To confirm the pressure drop as predicted by Bernoulli, the inlet andoutlet of the pump were connected to the reservoir and the pressuresensor was zeroed in the absence of fluid flow. The pump was turned onto introduce fluid flow into the system. Once the system had reached asteady state condition, a pressure measurement was taken. Pressure dropmeasurements were taken for fluid flow rates from 0 to 6 LPM. The datawas fit to a 2nd polynomial in an effort to determine if experimentwould match classical theory. To assist the curve-fit, the data wasmirrored along the y-axis prior to fitting.

Experimental data fit a 2nd order polynomial very well, with typicalstandard deviations from the fit in the range of 0.05-0.10. However, thePressure Drop Coefficient did not match classical theory. FIG. 5 is agraph that displays both expected and experimental results from thepressure drop data.

It was hypothesized that a boundary-layer effect was occurring in theexperiment, resulting in little to no flow at the inside walls of thetubing. If this were true, a majority of the flow was occurring in themiddle portion of the tubing, resulting in a greater pressure drop thanexpected.

To test this hypothesis, a 2″ ID 6″ long section of PVC pipe wasinserted inline with the tubing, and a pressure sensor was attached tothe side of the PVC pipe. In this case, classical physics predictsuniform flow distribution through the cylinder, reducing the velocity ofthe fluid such that the pressure drop would be miniscule. Results ofthis test showed that the 2″ ID tubing had almost no effect on themeasured pressure drop. This confirmed that fluid flow was occurring inthe middle of the tubing, and that the fluid near the perimeter of thetubing was merely acting as a buffer to transfer the pressure signal.

After further experimentation varying parameters such as tubing size,pressure sensor coupler length, pressure sensor attachment mechanism,and distance from the reservoir, it became obvious that the physicalconfiguration of the pressure sensor and the tubing affected theresults. In particular, variations in distance from the reservoir seemedto have the greatest effect on the Pressure Drop Coefficient. Varyingthe aforementioned parameters resulted in Pressure Drop Coefficientsfrom 0.15 to 0.35 inH2O-min2/L2. These results are displayed in FIG. 6.

Fluid Mechanics distinguished two types of flow for a viscous fluid:laminar and turbulent. In distinguishing between the two types of flow,a dimensionless constant called Reynolds's number is introduced. AReynold's number of less than 2000 implies laminar flow, whereas anumber over 4000 implies turbulent flow, and values between 2000 and4000 represent a transition area. Reynold's number is defined asfollows:

Re=ρVD/μ,

where V is fluid velocity, D is pipe diameter, ρ is fluid density, and μis fluid viscosity.

For the ⅜″ ID tubing used in this test, Reynold's number falls in thelaminar region only for fluid flows of less than 1 LPM. Thus, turbulentflow must be considered and applied to this test. Experimentation is theprimary means by which turbulent fluid flow characteristics aredescribed, and because turbulence is so complex, its complete analysisand quantification will probably never be achieved.

In researching the area of turbulent fluid mechanics, an effect termedthe “entrance effect” was encountered. The effect defines a criticaldistance Le at which fully developed flow occurs at the entrance to aconduit from a reservoir. The effect occurs due to shear where a fluidenters the conduit from a reservoir. FIG. 7 demonstrates this effect.

For turbulent fluid flow, experimentation has shown that the entrancelength can be approximated to:

L _(e) /D˜4.4Re ^(1/6).

Applying this relationship to the test implies that entrance effectscould prevent fully-developed fluid flow for a distance of about 9″ fromthe reservoir outlet. Considering these findings, experiments wereconducted that measured the Pressure Drop Coefficient at variousdistances from the reservoir outlet. Each Pressure Drop Coefficient wasdetermined using pressure/flow data fit to a 2nd order polynomial atdistances from 6 to 26 inches from the reservoir outlet in 4″increments. FIG. 8 shows that the Pressure Drop Coefficients increasedlinearly with distance out to 26 inches.

Because a perfusion circuit will not tolerate the application of apressure sensor very far from the venous reservoir's outlet, it was notbeneficial to pursue entrance effects beyond a distance of 26 inches.

Analysis of pressure drop experimentation revealed that the pressuredrop could not be accurately predicted from theory alone. However, ifphysical conditions are kept constant, the pressure drop responds tovarious flow rates in a very consistent parabolic fashion. With thisdata in hand, two recommendations can be made: (1) A preferred physicalconfiguration may be defined and characterized, e.g., a containerprofile, and (2) a single pressure datapoint can be taken whilemaintaining constant volume in the reservoir. From this singledatapoint, the coefficient of pressure drop can be determined. Thisdatapoint should be taken at a high flow rate so that the Flow² term isemphasized, and a more accurate Pressure Drop Coefficient can beattained.

In a second test, the 1500 ml Sams flexible venous reservoir was filledwith 750 mL of fluid, and a datapoint was taken at 6 LPM to generate aPressure Drop Coefficient that would be used throughout the systemintegration testing. The reservoir was then filled with 1250 ml offluid, and a centrifugal pump was connected such that it was drawingfluid from the reservoir's outlet, and pumping back into the inlet.

Volume data was generated and gathered at flow rates of 0, 1, 2, 3, 4,5, and 6 LPM. After each series of data was gathered, 250 ml of fluidwere drawn out of the system, and data was gathered again. This wasrepeated until there were only 250 ml of fluid left in the reservoir.Percentage error between the actual and detected volumes was generatedfor the various flow and volume conditions, and this data is plotted inFIG. 9.

FIG. 9 shows that the system was most accurate at 750 ml. This may beexpected for two reasons: (1) this is the most linear region from theReservoir Pressure-Volume Characterization as seen in FIG. 4; and (2)the pressure drop coefficient was sampled at 750 ml, effectively“tuning” the system for this volume.

Although it was expected that the high flow rates of 5 and 6 LPM wouldgenerate more error, they did not. These results demonstrate just howclosely the pressure drop curve fit matches the actual pressure dropacross various flow rates.

In a third test, a model was developed in which a peristaltic rollerpump drives the cardiopulmonary bypass circuit. This pump does notproduce a steady flow of fluid; rather it acts more like a human heartby injecting fluid at spaced intervals. This type of pump adds pressurenoise to the system. The pressure sensor not only senses the pressureexerted by the level of the static fluid, it also senses the pressurenoise. The output from the pressure will be digitally sampled so it mustfirst pass through an analog anti-alias filter. Because the signal willbe sampled at 250 Hz, the low-pass cutoff of the filter was 125 Hz. Thesignal was then passed to the analog to digital converter and sampled. A12 bit ADC from National Instruments was used in this test. This digitaldata was then passed into LabVIEW where it can be processed. Inaddition, a Hall-Effect device was connected to the rotating shaft ofthe roller pump. A distinct pulse was generated each time the pump makesa full rotation. This signal was simultaneously passed into LabVIEWwhere it can also be processed. Finally, the processed information,including the level of the bag and the speed of the pump, was output toa user controlled display panel.

The first part of this test was the removal of the pressure noise addedby the roller pump. The upper left corner of FIG. 10 shows the unusablesignal with the pressure noise added by the pump. The frequency analysisshown in the bottom left corner of FIG. 10 shows the frequency contentof the noise. From this information a filtering scheme was developed.FIG. 10 shows the actual signal and the spectrum before and afterlow-pass filtering. The filtering was done digitally in real-time withLabVIEW. The cutoff of the Butterworth low-pass was 0.3 Hz with a fourthorder response.

As FIG. 10 shows, the system was effective at removing the pressurenoise and generating a quiet pressure signal.

A method was examined for obtaining tachometer information withoutadding hardware to the system from the original pressure pulses. Eachtime a roller in the pump passed the tube it would generate a peak inthe signal. If the time between these peaks could be determined, thetachometer information would be known. However, in some environments,the pulses may not be consistent enough to generate tachometerinformation. The wave-shape of four consecutive pressure pulses wasshown in FIG. 11.

For this test, Honeywell Series 160 PC Differential Pressure Sensor(0-10″ Water) was used. In addition, a low pass analog butterworthfilter with cutoff frequency of 125 Hz, a peristaltic roller pump fromCole-Parmer (Drive: EW 07593 Head: EW07019), a hall effect switch(UGN-3013T Hall Effect Digital Switch), and LabVIEW (A/D Fs 250 Hz)display panel were used. The fluid used in this experiment was water asthe density of water is similar to that of blood.

FIG. 12 illustrates a circuit diagram of an active filter. This filterhas a cutoff frequency of 125 Hz with a third order Butterworthresponse. The signal is being sampled at 250 Hz, so it may be desirableto keep frequencies of greater than 125 Hz out of the signal. Anotherfilter design would have set the cutoff frequency around 50 Hz. This mayhave ensured that all frequencies at 125 Hz or higher would have beenfully attenuated, not only 3 dB of attenuation as this filter provides.This did not cause any problems for this test because the actual signaldid not have any frequency content higher than 45 Hz.

The actual digital pulses used for the timing of the tachometer areshown in FIG. 13. The signal stays high until the magnet on the rotatingshaft passes the Hall Effect Device. This method allowed for aconsistent and accurate tachometer at the expense of the addition ofmore hardware and more wires.

Several variations were tested to ensure consistent results. Theseexperiments included: varying the speed of the pump, moving the sensorin relation to the bag, using different size blood bags, and changingthe length of the tubing connected to the sensor. None of thesevariations caused discrepancies.

Various embodiments of the invention have been described. For example,although described in reference to detection of blood within a venousreservoir of a cardiopulmonary bypass circuit, the techniques may beapplied to IV pumps, dialysis machines, cardiac assist systems,arthroscopy systems, and the like. These and other embodiments arewithin the scope of the following claims.

1. A medical system comprising: a fluid circuit having a reservoir; apressure sensor coupled within the fluid circuit near an outlet of thereservoir, wherein the pressure sensor generates a pressure signalrepresentative of a sensed pressure of the fluid circuit; a controllerthat computes a volume of fluid within the reservoir as a function ofthe pressure signal and a flow signal representative of a fluid velocityof the fluid exiting the reservoir, the controller configured to outputan indicator based on the computed volume; and a memory programmed tostore a set of container profiles, wherein the controller selects one ofthe container profiles for the reservoir and computes the volume basedon the selected profile, and further wherein the container profilescomprise one or more coefficients that are applied by the controller tocompute the volume.
 2. The medical system of claim 1, wherein the fluidcircuit is a cardiopulmonary bypass circuit, and wherein the flexiblereservoir is a venous reservoir of the cardiopulmonary bypass circuit.3. The medical system of claim 1, further comprising a flow sensorcoupled within the fluid circuit that generates the flow signal.
 4. Thesystem of claim 1, wherein the controller applies a polynomial to mappressure to volume.
 5. The system of claim 4, wherein the one or morecoefficients of each container profile are associated with a respectivetype of container, and the controller applies the coefficients of theselected container profile to evaluate the polynomial.
 6. The system ofclaim 1, wherein at least one of the container profiles corresponds to aflexible container.
 7. The system of claim 1, wherein at least one ofthe container profiles corresponds to a hard container.
 8. The system ofclaim 1, wherein the controller comprises an input device to receiveinput from a user for selecting the container profile.
 9. The system ofclaim 1, wherein the controller comprises an input device to receivepatient-specific parameters from a user, and wherein the controllercomputes the volume as a function of the patient-specific parameters.10. The system of claim 1, wherein the reservoir is a reservoir within afluid circuit of an IV pump.
 11. The system of claim 1, wherein thereservoir is a reservoir within a fluid circuit of a dialysis machine.12. The system of claim 1, wherein the reservoir is flexible reservoirwithin a fluid circuit of a cardiac assist system.
 13. The medicalsystem of claim 1, wherein the reservoir is reservoir within a fluidcircuit of an arthroscopy system.
 14. A method comprising: generating aset of container profiles, wherein each container profile is associatedwith a particular type of container that can be used as a reservoirwithin a medical system, and further wherein the container profilescomprise one or more coefficients; storing the set of container profileswithin a memory; generating a pressure signal representative of apressure in a fluid circuit of the medical system at a location near anoutlet of a reservoir; selecting one of the container profiles for thereservoir; computing a volume of fluid within the reservoir as afunction of the pressure signal based on the selected container profile,wherein the coefficients of the selected container profile are appliedto compute the volume; and outputting an indicator based on the computedvolume.
 15. The method of claim 14, further comprising generating a flowsignal representative of a fluid velocity of the fluid exiting thereservoir, wherein computing a volume comprises computing the volume asa function of the flow signal and the pressure signal.
 16. The method ofclaim 14, wherein the fluid circuit is a cardiopulmonary bypass circuit,and wherein the flexible reservoir is a venous reservoir of thecardiopulmonary bypass circuit.
 17. The method of claim 14, whereincomputing the volume comprises evaluating a polynomial that mapspressure to volume in accordance with the selected container profile.18. The method of claim 17, wherein the coefficients of each of thecontainer profiles are associated with a respective type of container,and wherein evaluating a polynomial comprises applying the coefficientsdefined by the selected container profile to evaluate the polynomial.19. The method of claim 14, wherein at least one of the containerprofiles corresponds to a flexible container.
 20. The method of claim14, wherein at least one of the container profiles corresponds to a hardcontainer.
 21. The method of claim 14, further comprising: receivinginput from a user indicating a type of container; and selecting thecontainer profile based on the input.
 22. The method of claim 14,further comprising: receiving patient-specific parameters from a user;and computing the volume as a function of the patient-specificparameters.
 23. The method of claim 14, wherein the reservoir is areservoir within a fluid circuit of an IV pump.
 24. The method of claim14, wherein the reservoir is a reservoir within a fluid circuit of adialysis machine.
 25. The method of claim 14, wherein the reservoir isflexible reservoir within a fluid circuit of a cardiac assist system.26. The method of claim 14, wherein the reservoir is reservoir within afluid circuit of an arthroscopy system.
 27. A method comprising: storingthe set of container profiles within a memory, wherein each containerprofile is associated with a particular type of container that can beused as a reservoir within a fluid circuit of a medical system, andfurther wherein the container profiles comprise one or morecoefficients; selecting one of the container profiles for the reservoir;receiving a pressure signal representative of a pressure in the fluidcircuit at a location near an outlet of the reservoir; computing avolume of fluid within the reservoir as a function of the pressuresignal based on the selected container profile, wherein the coefficientsof the selected container profile are applied to compute the volume; andautomatically generating a pump control signal based on the computedvolume to control the volume of fluid within the reservoir.